Uplink power control scheme

ABSTRACT

An uplink power control technique may include a simplified maximum sector throughput (SMST) and a generalized maximum sector throughput (GMST). The SMST and GMST techniques may be used to determine a maximum sector throughput and cell-edge throughput to enhance the overall efficiency of the communication system. The uplink power control technique may determine the optimal uplink power value without collecting interference over thermal noise and without computing the individual channel losses in each neighboring sector.

CROSS-REFERENCE OF RELATED APPLICATIONS

This application is a continuation of, claims the benefit of and priority to, previously filed U.S. patent application Ser. No. 12/630,673 entitled “An Uplink Power Control Scheme” filed on Dec. 3, 2009, the subject matter of which is hereby incorporated by reference in its entirety.

BACKGROUND

Uplink power control may be used to control the transmit power level to balance the link performance, terminal battery power, and reduce the inter-sector co-channel interference in uplink. Techniques such as open loop power control (OLPC) and closed loop power control (CLPC) may be used to control uplink power. Open loop power control may be based on channel loss estimation and the broadcasted information and is generally used for slow power control. Closed loop power control may be used for fast power control with high signaling overhead induced by unicast control signal.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention described herein is illustrated by way of example and not by way of limitation in the accompanying figures. For simplicity and clarity of illustration, elements illustrated in the figures are not necessarily drawn to scale. For example, the dimensions of some elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference labels have been repeated among the figures to indicate corresponding or analogous elements.

FIG. 1 illustrates an environment 100, which may support maximum sector throughput technique to maximize sector throughput and cell edge throughput in accordance with one embodiment.

FIG. 2 illustrates a block diagram of a mobile node, which may support simplified maximum sector throughput (SMST) and generalized maximum sector throughput (GMST) techniques to maximize sector throughput and cell edge throughput in accordance with one embodiment.

FIG. 3 is a flow-chart, which depicts a maximum sector throughput technique in accordance with one embodiment.

FIG. 4 is a flow-chart, which depicts a technique to determine spectral efficiency (SE) gain in a home sector supporting a home mobile node in accordance with one embodiment.

FIG. 5 is a flow-chart, which depicts a technique to determine spectral efficiency (SE) loss in a virtual sector representing neighboring nodes in accordance with one embodiment.

FIG. 6 illustrates a table 600, which includes parameter-value combination that reflects the performance of a maximum sector throughput technique in accordance with one embodiment.

FIG. 7 is a graph 700, which depicts a relationship between cumulative density function (CDF) and throughput in accordance with one embodiment.

FIG. 8 illustrates a table 800 in which spectral efficiency derived for various uplink power control techniques are compared in accordance with one embodiment.

FIG. 9 illustrates a radio system 900, which may support the uplink power control schemes in accordance with one embodiment.

DETAILED DESCRIPTION

The following description describes embodiments of an uplink power control schemes in broadband wireless networks. In the following description, numerous specific details such as transceiver implementations, resource partitioning, or sharing, or duplication implementations, types and interrelationships of system components are set forth in order to provide a more thorough understanding of the present invention. It will be appreciated, however, by one skilled in the art that the invention may be practiced without such specific details. In other instances, control structures, gate level circuits, and full software instruction sequences have not been shown in detail in order not to obscure the invention. Those of ordinary skill in the art, with the included descriptions, will be able to implement appropriate functionality without undue experimentation.

References in the specification to “one embodiment”, “an embodiment”, “an example embodiment”, indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

In one embodiment, a uplink power control technique referred to as maximum sector throughput (MST) technique may be used to maximize the sector throughput and cell edge user throughput. In one embodiment, the MST technique may provide uplink power control without using interference over thermal (IoT) noise. In one embodiment, the MST technique may determine spectral efficiency SE_(Gain) for mobile nodes in the home sector after determining a new transmit power (P_(New)) by incrementing a current transmit power value (P₀) by an incremental transmit power value (ΔP) using a slow fading technique to determine signal to interference plus noise ratio (SINR). In one embodiment, the SINR may be determined without using instantaneous channel realization, which may be estimated in advance, which may require substantial computational resources and cause processing delay.

In one embodiment, SE_(Loss, E) may be determined in a virtual neighboring sector that may represent an aggregate of interferences suffered by the neighboring sectors (1 to N) in response to increasing the transmit power of the home mobile node. In one embodiment, the SE_(Loss, E) may be determined without using downlink preambles sent from the neighboring base stations (BS) and noise plus interference level (NI) exchanged and broadcasted among neighboring BS. In one embodiment, the SE_(Gain) and SE_(Loss, E) may be used to determine an optimal power P_(Tx) ^(opt) to maximize the overall throughput. In one embodiment, the SE_(Gain) and SE_(Loss, E) may be further used to enhance cell edge throughput as well.

An embodiment of an environment 100 in which maximum sector throughput (MST) technique may be used to maximize sector throughput and cell-edge throughput is illustrated in FIG. 1. In one embodiment, the environment 100 may comprise home sector 101, neighboring sectors 102-A to 102-D, and a virtual sector 170. In one embodiment, the home sector 101 may include a home mobile node (HMN) 105. In one embodiment, the HMN 105 may include a cell phone, smart phone, personal digital assistant (PDA), mobile internet devices (MIDs), laptops, and such other computing systems. In one embodiment, the sector 101 is shown comprising a cell phone 105 as an example. In one embodiment, the HMN 105 may represent any device, which may support wireless technologies such as third generation partnership project (3GPP), worldwide interoperability for microwave access (WiMAX), and long term evolution (LTE).

In one embodiment, the HMN 105 may use a variety of multiple access techniques such as frequency division multiplexing (FDM), time division multiplexing (TDM), coded division multiplexing (CDM), orthogonal frequency division multiplexing (OFDM), and single carrier frequency division multiplexing (SC-FDM) and others. In one embodiment, the HMN 105 may be coupled to a home base station HBS 110. In one embodiment, the home sector 101 may be surrounded by neighboring sectors 102-A to 102-D, which may, respectively, comprise neighboring mobile nodes 120-A to 120-D. In one embodiment, the neighboring mobile nodes 120-A to 120-D may be, respectively, coupled to neighboring base stations NBS 130-A to 130-D.

In one embodiment, the HMN 105 may be provided with a current transmit power value (P₀) to transmit information packets to a destination mobile node provisioned either within the home sector 101 or the neighboring sectors 102-A to 102-D. In one embodiment, the HMN 105 may send the information packets to the HBS 110. In one embodiment, to enhance the uplink performance such as sector throughput and cell edge throughput within the home sector 101, the uplink transmit power may be increased by incrementing the current transmit power value (P₀) by a incremental power value (ΔP) to cause a new transmit power value (P_(New)). However, increasing the uplink transmit power value to a new transmit power value (P_(New)) may cause interference to NMN 120-A, 120-B, 120-C and 120-D, which may be operating in a same frequency channel in the neighboring sectors 102-A to 102-D, respectively, and may decrease the link performance in the neighboring sectors 102-A to 102-D.

In one embodiment, the MST technique described below may be used to balance link performances in the home sector 101 and neighboring sectors 102 to maximize overall sector throughput and cell edge throughput. In one embodiment, to predict the effective SE_(Loss, E) in all neighboring sectors 102, a virtual sector such as the virtual sector 170 may be used. In one embodiment, the aggregate of interferences caused by the new transmit power value (P_(New)) on the base station VBS 160 may provide an estimate of effective SE_(Loss, E).

An embodiment of the HMN 105, which may support techniques to maximize sector throughput and cell edge throughput is illustrated in FIG. 2. In one embodiment, the HMN 105 may comprise an interface 201, a controller 205, a power management block 309, one or more transceivers 210-A to 210-N, a switch 230, and an antenna 290. In one embodiment, the block diagram 200 may be a provisioned as a portion of a network interface card in other scenarios such as a computer platform, a laptop computer, a mobile internet device, handhelds, smart phones, televisions and such other systems.

In one embodiment, the interface 201 may couple the HMN 105 to the home base station HBS 110. In one embodiment, the interface 201 may provide physical, electrical, and protocol interface between the HMN 105 and the other blocks. In one embodiment, the controller 205 may maintain a track of the transceivers 210 that may be operational. In one embodiment, the controller 205 may control the modulation and demodulation techniques selected by the transceivers 210. In one embodiment, the controller 205 may control communication parameters such as the transmission rate, bit error rate, and other such parameters.

In one embodiment, the transceiver 210-A may comprise a transmitter 250 and a receiver 270. In one embodiment, each of the transceiver 210-B to 210-N may comprise a transmitter and receiver similar to the transmitter 250 and the receiver 270 of the transmitter 210-A. In one embodiment, while receiving the signals from the antenna 290, the receivers such as the receiver 270 of the transceivers 210-A to 210-N, may receive the signal from the antenna 290 through a switch 230. In one embodiment, while transmitting the signals, the transmitters such as the transmitter 250 of the transceivers 210 may provide the radio signal to the antenna 290 through the switch 230.

In one embodiment, the transmitter 250 may receive signals to be transmitted from the controller 205 or directly form the interface 201 under the control of the controller 205. In one embodiment, the transmitter 250 may modulate the signals using techniques such as phase, or amplitude, or frequency modulation techniques. In one embodiment, the transmitter 250 may then transmit the signals to the antenna 290 through the switch 230. In one embodiment, the receiver 270 may receive electrical signals from the antenna 290 and demodulate the signals before providing the demodulated signals to the controller 205 or directly to the interface 201.

In one embodiment, the switch 230 may couple a transmitter of the transmitters 210 to the antenna 290 on time sharing basis, for example. In one embodiment, the switch 230 may couple a specific transceiver 210 to the antenna 290 in response to an event such as a selection control signal of the controller 205. In other embodiment, the switch 230 may be provided with intelligence to couple an appropriate transmitter 210 to the antenna 290. In one embodiment, the switch 230 may couple the antenna 290 to the transmitter 250 while the transmitter 250 may be ready to transmit signals out to a receiver in other system. In one embodiment, the switch 230 may couple the antenna 290 to the receiver 270, while the antenna 290 has generated signals to be provided to the receiver 520. In one embodiment, the antenna 590 may be coupled to a switch 530.

In one embodiment, the power management block 209 may support a MST technique to determine an optimal transmit power to maximize the sector throughput and the cell edge throughput. In one embodiment, the power management block 209 may provide a current transmit power value (P₀) to the transmitter 250 to enable the transmitter 250 to transmit information packets. In one embodiment, the value of P₀ may be based on a desired link performance. In one embodiment, the power management block 290 may increase the uplink transmit power value by incrementing the current transmit power value (P₀) by a incremental power value (ΔP) to cause a new transmit power value (P_(New)). However, increasing the uplink transmit power value to a new transmit power value (P_(New)) may decrease the link performance in the neighboring sectors 102-A to 102-D by causing interference to NMNs 120-A, 120-B, 120-C and 120-D, which may be operating in a same frequency channel in the neighboring sectors 102-A to 102-D, respectively.

In one embodiment, the power management block 209 may use the MST technique described below to determine an optimal transmit power value, which may balance link performances in the home sector 101 and neighboring sectors 102 to maximize overall sector throughput and cell edge throughput. In one embodiment, the power management block 209 may determine the SE_(Gain) in the home sector 101 and predict the effective SE_(Loss, E) in all neighboring sectors 102 by aggregating the effective interference in a virtual sector 170. In one embodiment, the aggregate of interferences caused by the new transmit power value (P_(New)) on the base station VBS 160 may provide an estimate of effective SE_(Loss, E).

A flow-chart 300 depicting an operation of the HMN 105 to maximize sector throughput and cell edge throughput is illustrated in FIG. 3. In block 310, the power management block 209 may determine the new power value (P_(New)) by incrementing the current transmit power value (P₀) by an incremental power value (ΔP).

In block 350, without using interference over thermal (IoT) noise from the neighboring base stations NBS 102-A to 102-D, the power management block 209 may determine a spectral efficiency change value SE_(change) value. In one embodiment, the power management block 209 may compute the difference between the SE_(Gain) in the home sector 101 and effective SE_(Loss, E) in the neighboring sectors 102-A to 102-D represented as an aggregate or effective interferences in the virtual sector 170 in response to change in transmit power value from P₀ to P_(New) (=P0+ΔP). In one embodiment, determining SE_(Gain) and effective SE_(Loss, E) is depicted, respectively, in flow-chart 400 of FIG. 4 and flow-chart 500 of FIG. 5.

In block 370, the power management block 209 may check if the SE_(change) is equal to zero and control passes to block 380 if the SE_(change) has approached zero and to block 390 if the SE_(change) is a positive value. In block 380, the power management block 209 may use the new transmit power value P_(New) as the uplink transmit power value. In block 390, the power management block 209 may use the increment the new transmit power value P_(New) by adding an incremental power value, which may equal ΔP or any other such small value ΔP₁ and control passes to block 350.

A flow-chart 400 depicting an operation of the HMN 105 to determine SE_(Gain) is illustrated in FIG. 4. In block 410, the power management block 209 may determine an original Signal to Interference plus Noise Ratio (SINR_(Orig)) using a slow fading technique without collecting the instantaneous channel realization values. In one embodiment, the parameters that may be used to determine the SE_(Gain) may be as follows:

1) Channel Loss: The mobile node such as HMN 105 may enter a network (for example, by entering the home sector 101) and the channel loss between the HMN 105 and the HBS 110 may equal CL₀ represented by 141 and the channel loss between the HMN 105 and the neighboring NMS may equal CL_(i) (wherein ‘i’ may equal 120-A, 120-B, 120-C, 120-D, . . . 120-N) represented by 151, 152, 153, and 154. In one embodiment, the channel loss 151 may be determined using a downlink preamble received from the NBS 130-A. Likewise, the channel loss 152, 153, and 154 may be determined using downlink preambles received from the NBS 130-B, NBS 130-C, and NBS 130-D, respectively.

2) Noise plus Interference level (NI): At each neighboring base station, the NI may be estimated as sum power of noises and interferences at that neighboring base station. For example, the NI_130-A at NBS 130-A may be estimated using the information exchanged among the NBS 130 through a network backhaul. In one embodiment, the NI may be expressed in terms of Interference over Thermal (IoT) noise and noise in that sector as shown below in Equation (1): NI=IoT×P _(Noise) +P _(Noise)  Equation (1)

However, determining Channel Loss and NI may consume substantial computational resources and cause delay as well.

In one embodiment, the power management block 209 may determine the SE_(Gain) in response to increasing the uplink transmit power value to P_(New). In one embodiment, the SE_(Gain) in the home sector 101 may be given by the Equation (2) below: SE_(Gain)=log(1+SINR_(New))−log(1+SINR_(Orig))=log {(1+SINR_(New))/(1+SINR_(Orig))}  Equation (2)

In one embodiment, the power management block 209 may use a slow fading technique to compute SINR_(New) and SINR_(Orig) and the resulting SE_(Gain) may be substantially accurate based on the stochastic average. In one embodiment, the SINR_(Orig) (the signal plus interference noise ratio in the home sector 101) before increasing the current power value to a new power value may be given by Equation (3) below: SINR_(Orig)=(P ₀/CL₀)/NI₀  Equation (3)

In block 440, the power management block 209 may determine SINR_(New) after incrementing P₀ by ΔP to cause the new transmit power value P_(New) (=P₀+ΔP) using slow fading technique and without using instantaneous channel realization values. In one embodiment, the SINR_(New) (the signal plus interference noise ratio in the home sector 101) after increasing the current power value to a new power value P_(New) may be given by Equation (4) below: SINR_(New)={(P ₀ +ΔP)/CL₀)/NI₀}  Equation (4)

In block 480, the power management block 209 may determine SE_(Gain) using SINR_(New), and SINR_(Orig) determined, respectively, in Equations (3) and (4). In one embodiment, the SE_(Gain) may be given by Equation (5) below:

$\begin{matrix} \begin{matrix} {{SE}_{Gain} = {\log\left\{ {\left( {1 + {SINR}_{New}} \right)/\left( {1 + {SINR}_{Orig}} \right)} \right\}}} \\ {= {\log\begin{matrix} \left\{ {\left\lbrack {1 + \left( {{P_{New}/{CL}_{0}} \times {NI}_{0}} \right)} \right\rbrack/} \right. \\ \left. \left\lbrack {1 + \left( {{P_{0}/{CL}_{0}} \times {NI}_{0}} \right)} \right\rbrack \right\} \end{matrix}}} \\ {= {\log\left\{ {1 + {\left\lbrack \left( {\Delta\;{P/{CL}_{0}}} \right) \right\rbrack/\left\lbrack {{NI}_{0} + \left( {P_{0}/{CL}_{0}} \right)} \right\rbrack}} \right\}}} \end{matrix} & {{Equation}\mspace{14mu}(5)} \end{matrix}$

A flow-chart 500 depicting an operation of the HMN 105 to determine effective SE_(loss, E) is illustrated in FIG. 5. In block 510, the power management block 209 may determine an equivalent channel loss (CL_(E)) from the HMN 105 to the virtual sector 170, which may suffer aggregate interferences in the neighboring sectors 102-A to 102-D caused by providing P_(New) to HMN 105.

To predict the channel loss in the neighboring sectors 102, the power management block 209 may need 1) Channel Loss from HMN 105 to each of the NBS 130-A to 130-D; (2) NI for each of the NBS 130-A to 130-D; and (3) uplink transmit power of each NMN 120-A to 120-D provisioned in the neighboring sectors 102-A to 102D, respectively. However, to obtain channel loss in each sector, the downlink preamble sent from each NMN 120-A to 120-D may be used. Also, NI_(i) may be first exchanged between the NBS 130-A to 130-D and then broadcasted. To obtain channel loss (CL_(i)) and (NI_(i)) for each NBS 130-A to 130-D, a complex hardware may be needed in addition to incurring high feedback overhead and computationally intensive operations. Also, it may be unrealistic to obtain the uplink transmit power value of the NMN 120-A to 120-D, as the NMN 120-A to 120-D may be attempting to increment the uplink transmit power values.

In one embodiment, to overcome the above disadvantages, the power management block 290 may determine the equivalent channel loss (CL_(E)) from the HMN 105 to the virtual sector 170 (or VBS 160) and CL_(E) may be given by Equation (6) below: Interference=P ₀/CL_(E)=Σ_((i=1 to N)) P ₀/CL_(i) →CL_(E)=(Σ_(i=1 to N))1/CL_(i))⁻¹  Equation (6)

In one embodiment, the following approximations may be made before determining SE_(Loss, E);

Approximation (1): The equivalent channel loss (CL_(E)) may be determined by estimating the CINR for downlink preamble as compared to determining the channel loss (CLi) for each NBS 130-A to 130-D.

Approximation (2): Also, effective signal to noise ratio (SNR_(E)) in the virtual sector 170 may be substantially same as the average signal to noise ratio (SNR_(Avg, home),) in the home sector 101 as the average SNR levels in the different sectors 102-A to 102-D may not vary at all or may vary little to be significant. In one embodiment, the relationship between the SNR_(E) and SNR_(Avg home) is as shown in Equation (7) below: SNR_(E)=SNR_(Avg, home)  Equation (7)

Approximation (3): Also, effective noise plus interference ratio (NI_(E)) in the virtual sector 170 may be approximated to noise plus interference ratio (NI₀) in the home sector 101. In one embodiment, the relationship between the NI_(E) and NI₀ is as shown in Equation (8) below: NI_(E)=NI₀  Equation (8)

In block 540, the power management block 209 may determine an equivalent original SINR (SINR_(E, Orig)) without determining the channel loss (CLi) for each neighboring sector 102-A to 102-D individually and without using the NI, information from the neighboring sectors 102-A to 102-D. In one embodiment, the SINR_(E, Orig) (the effective signal plus interference noise ratio in the virtual sector 170) before increasing the current power value to a new power value may be given by Equation (9) below: SINR_(E, Orig)=(SNR_(E) *P _(Noise))/NI_(E)  Equation (9)

In block 550, the power management block 209 may determine SINR_(E, New) at the virtual sector 170 (or VBS 160) after incrementing P₀ by ΔP to cause the new transmit power value P_(New) (=P₀+ΔP). In one embodiment, the SINR_(E, New) (the signal plus interference noise ratio in the virtual sector 170) after increasing the current power value to a new power value P_(New) may be given by Equation (10) below: SINR_(E, New)={(SNR_(E) *P _(Noise))/(NI_(E) +ΔP/CL_(E))}  Equation (10)

In block 580, the power management block 209 may determine an equivalent SE_(Loss,E) using SINR_(E, New) and SINR_(E, Orig) determined, respectively, in Equations (9) and (10). In one embodiment, the SE_(Loss,E) may be given by Equation (11) below:

                                Equation  (11) $\begin{matrix} {{SE}_{{Loss},E} = {\log\left\{ {\left( {1 + {SINR}_{E,{New}}} \right)/\left( {1 + {SINR}_{E,{Orig}}} \right)} \right\}}} \\ {= {\log\begin{matrix} \left\{ {\left\lbrack {1 + \left( {{SNR}_{E}*{P_{Noise}/{NI}_{E}}} \right)} \right\rbrack/} \right. \\ \left. \left\lbrack {1 + \left( {{{SNR}_{E}*{P_{Noise}/{NI}_{E}}} + {\Delta\;{P/{CL}_{E}}}} \right)} \right\rbrack \right\} \end{matrix}}} \\ {= {\log\begin{matrix} \left\{ {1 + {\left\lbrack {\left( {{SNR}_{{Avg},{home}}*P_{Noise}} \right)/{NI}_{0}} \right\rbrack/}} \right. \\ \left. \left\lbrack {\left( {{SNR}_{{Avg},{home}}*P_{Noise}} \right)/\left( {{NI}_{0} + {\Delta\;{P/{CL}_{E}}}} \right)} \right\rbrack \right\} \end{matrix}}} \end{matrix}$

In one embodiment, the power management block 209 may determine the optimal transmit power P(Optimal). In one embodiment, if the increase in P_(New) leads to a positive SE_(change), the overall sector throughput may increase and the current power value may be incremented until a negative SE_(change) may be anticipated. In one embodiment, the optimal transmit power P(Optimal) may be achieved while SE_(change) equals zero and ΔP tends to zero. In one embodiment, the SE_(change) may be given by Equation (12) below:

$\begin{matrix} {\mspace{79mu}{{{SE}_{change} = {{{SE}_{Gain} - {SE}_{Loss}} = {0\left( {\Delta\; P}\rightarrow 0 \right)}}}\begin{matrix} {{P({Optimal})} = {\log\left\{ {1 + \left\lbrack {\left( {\Delta\;{P/{CL}_{0}}} \right)/\left( {{NI}_{0} + {P_{0}/{CL}_{0}}} \right)} \right\rbrack} \right\}}} \\ {= {\log\left\{ {\left\lbrack {1 + {\left( {{SNR}_{E}*P_{Noise}} \right)/{NI}_{E}}} \right\rbrack/} \right.}} \\ \left. \left\lbrack {1 + {\left( {{SNR}_{E}*P_{Noise}} \right)/\left( {{NI}_{E} + {\Delta\;{P/{CL}_{E}}}} \right)}} \right\rbrack \right\} \end{matrix}\begin{matrix} {{P({Optimal})} = {\quad\left\lbrack {{CL}_{E} \times {NI}_{0} \times {\left( {{NI}_{0} + {{SNR}_{{Avg},{home}} \times P_{Noise}}} \right)/}} \right.}} \\ {\left. \left. {{SNR}_{{Avg},{home}} \times P_{Noise}} \right) \right\rbrack - {{CL}_{0} \times {NI}_{0}}} \end{matrix}}} & {{Equation}\mspace{14mu}(12)} \end{matrix}$

In one embodiment, the uplink power control technique discussed above may be referred to Simplified Maximum Sector Throughput (SMST) technique. In one embodiment, a Generalized Maximum Sector Throughput (GMST) technique may be derived from Equation (12) above.

                                     Equation  (13) $\begin{matrix} {\left\lbrack {{{P({Optimal})}/{CL}_{0}} \times {NI}_{0}} \right\rbrack = {\left( {{CL}_{E}/{CL}_{0}} \right) \times \left\lbrack {1 + \left( {1/} \right.} \right.}} \\ {{\left. {{SNR}_{{Avg},{home}} \times {P_{Noise}/{NI}_{0}}} \right) - 1},} \\ {= {SINR}_{Target}} \\ {= \left\{ {{{CINR}_{Preamble} \times \left\lbrack {1 + \left( {1/{SINR}_{{Avg},{home}}} \right)} \right\rbrack} - 1} \right\}} \end{matrix}$

wherein CINR_(Preamble)=(CL_(E)/CL₀); SINR_(Target)=[P(Optimal)/CL₀×NI₀]; and SINR_(Avg,home)=(SNR_(Avg,home)×P_(Noise)/NI₀). From Equation (13), it may be seen that GMST technique may be based on SINR_(Target). In one embodiment, a carrier to interference plus noise ratio for a downlink preamble (CINR_(Preamble)) maybe used to measure the tradeoff between channel loss compensation for home sector 101 and neighboring sectors 102-A to 102-D IoT control. In one embodiment, as the SINR_(Target) may rely on CINR of downlink preamble, the power management block 209 may not estimate individual CL_(i), which may reduce the complexity of the GMST technique substantially.

Also, in one embodiment, the SINR_(Target) may have a fixed relationship with the CINR_(Preamble) and as an extension other tunable parameter coefficients may be used. In one embodiment, the Equation (14) below may provide an expression for a Generalized Maximum Sector Throughput (GMST) technique. SINR_(Target)=β×(CINR_(Preamble))^(γ)+α  Equation (14)

wherein ‘γ’ (gamma) may be used for fractional channel loss compensation. By comparing, Equation (13) and Equation (14), it may be seen that SMST technique may be a particular case of GMST technique with α (alpha)=−1, β(beta)=1+(1/SINR_(Avg,home)), and γ=1. In one embodiment, the GMST technique may achieve improved cell-edge throughput by tuning the parameter set (α, β, γ).

In one embodiment, a low value of SINR_(Target) may reduce the throughput of users at the edge of the cell and a high value of SINR_(Target) may increase the interference in neighboring sectors. In one embodiment, to improve the cell-edge throughput the SINR_(Target) may be limited as shown in Equation (15) below: SINR_(Min)<=SINR_(Target)<=SINR_(Max)  Equation (15)

From Equation (13), the SINR_(Target) may be determined as shown in Equations (16) and (17) below: SINR_(Target)=Max{SINR_(Min), CINR_(Preamble)×[1+(1/SINR_(Avg,home))]−1]  Equation (16) SINR_(Target)=Min{SINR_(Max), CINR_(Preamble)×[1+(1/SINR_(Avg,home))]−1]  Equation (17)

wherein SNIR_(Min) and SINR_(Max) may represent design parameters, which may be used to adjust the tradeoff between sector throughput and cell-edge throughput. In one embodiment, the power management block 209 may use SINR limitation and IoT control to improve the cell-edge throughput further. In one embodiment, the IoT level to the virtual sector 170 may be limited to be within a specific range and the limiting range is depicted in Equation (18) below: (P _(New)/CL_(i) ×P _(Noise))<=IoT_(Limit) →PNew<=(CLi×P _(Noise)×IoT_(Limit))  Equation (18)

wherein IoT_(Limit) may be used as another tunable parameter while designing a communication system.

A table 600 includes a list of parameter-value combination that may be used to evaluate the performance of the SMST and GMST techniques in accordance with one embodiment. In one embodiment, the table 600 may comprise two columns-parameter list 610 and value 650. In one embodiment, the parameter list 610 and the corresponding values 650 may comprise bandwidth (=10 Mhz) for each sector, frequency reuse (=1), cell deployment (=3 sectors and 19 cell wrap-around), number of users (10/sector), number of strong interference (=8), channel model (=E-ITUPed B 3 km/h), permutation mode (=WiMax UL), Uplink symbols (=15), and the site-to-site distance (=500 meters). In one embodiment, using the above listed parameters and the values, the following techniques may be evaluated:

-   -   T1: Maximum power technique: All mobile nodes 105 and 120-A to         120-D may use full power without any power control mechanism;     -   T2: SNR-target based technique: Power may be set such that the         received SNR at the base stations may attain a predefined target         i.e., P₀=SNR_(Target)×P_(Noise)×CL₀, wherein SNR_(Target)=7 db;     -   T3: SMST+SINR_(Min)+SINR_(Max) technique: wherein SINR_(Min)=0         db and SINR_(Max)=20 db;     -   T4: SMST+IoT_(Limit) technique: wherein IoT_(Limit)=7 db;     -   T5: SMST+SINR_(Min)+IoT_(Limit) technique: wherein SINR_(Min)=0         db and IoT_(Limit)=7 db;     -   T6: GMST technique: wherein α (alpha)=−0.9, β (beta)=−0.64, and         γ (gamma)=0.9;

A graph 700 depicting a relationship between the cumulative density function (CDF) and throughput for the above listed techniques T1 to T6 is illustrated in FIG. 7. In one embodiment, the throughput in kilobytes per second (kbps) may be plotted along the x-axis 705, and the CDF may be plotted along the Y-axis 795. In one embodiment, the plot 710, 720, 730, 740, 750, and 760 illustrate a relationship between CDF and throughput while using techniques T1 to T6, respectively. As depicted in the plots, the plot 760 for a GMST technique provides maximum CDF and throughput and plots SMST based techniques with SINR_(Min) and SINR_(Max) limitations combined with IoT_(Limit) may provide substantially similar CDF and throughput values as may be seen from plots 730, 740, and 750. However, from plot 710, the maximum power technique may provide lesser throughput as compared to SMST based technique and GMST technique. The plot 720 based on SNT Target may provide high CDF response but very low throughput. In one embodiment, the SMST based techniques (T3, T4, and T5) and GMST technique T6 may be used to achieve maximum sector throughput and cell-edge throughput as well as compared to maximum power technique and SNR_(Target) techniques.

A table 800 depicting a spectral efficiency (SE) comparison chart for sector and cell-edge conditions achieved using the techniques T1 to T6 is illustrated in FIG. 8. In one embodiment, the table 800 may comprise three columns—uplink power control (ULPC) technique 810, Sector SE 850, and 5% cell-edge SE 880. In one embodiment, the ULPC technique 810 may comprise techniques T1 to T6 listed above and the corresponding values of throughput in bits per second per Hertz for sector SE and cell-edge SE may be provided, respectively, in columns Sector SE 850 and 5% cell-edge SE 880.

In one embodiment, for SNR_(Target) technique, the cell-edge SE equaling 0.0369 (and throughput=141.3 kbps) may be maximum, however, the sector SE equals 0.4294 (and throughput=1.6444 Mbps), which may be lowest compared to other techniques. In one embodiment, for maximum power technique, the sector SE 850 may comprise a value of 0.5787 (and throughput=2.2163 Mbps) and cell-edge SE may equal 0.005 (throughput=19.3 kbps). In one embodiment, for SMST based techniques T3 to T5, the sector SE values may equal 0.7486 (throughput=2.867 Mbps), 0.7609 (throughput=2.9142 Mbps), and 0.7247 (throughput=2.7754 Mbps) and cell-edge SE may equal 0.0199 (throughput 76.3 kbps), 0.0082 (throughput=31.5 kbps), and 0.0216 (throughput=82.6 kbps). In one embodiment, for SMST based techniques T3 to T5, both the sector SE (and the throughput) and the cell-edge SE (and the throughput) may be optimal compared to it techniques T1 and T2. In one embodiment, for the GMST technique, the sector SE may equal 0.6426 (throughput=2.4612 Mbps) and cell-edge SE may equal 0.0339 (throughput may equal 129.8 kbps).

In one embodiment, the maximum power technique may result in lowest cell-edge throughput (=19.3 kbps) as interference may be out of control. In one embodiment, the SNR_(Target) technique may provide highest cell-edge throughput (=141.3 kbps) but at the cost of sector throughput (=1.6444 Mbps) as mobile nodes 105 and 120-A to 120-D may be forced to limit the maximum power to reduce interference. In one embodiment, the SMST based techniques T3 to T5 may achieve highest sector throughputs of 2.867 Mbps, 2.9142 Mbps, and 2.7754 Mbps, respectively. However, the cell-edge throughputs of 76.3 kbps, 31.5 kbps, and 62.6 kbps may be higher compared to the throughput for maximum power technique. In one embodiment, the GMST technique may provide an optimal sector throughput and cell-edge throughput.

An embodiment of a cognitive radio system 900, which may support SMST and GMST techniques to maximize sector and cell-edge throughput is illustrated in FIG. 9. In one embodiment, the cognitive radio system 900 may comprise a baseband 910, a signal transmitter 920, a signal receiver 930, a channel and power control block 940, a cognitive radio 950, a spectrum sensing receiver 970, a T/R switch 980, and an antenna 990.

In one embodiment, the antenna 990 may provide a wide frequency band. Such an approach may enable the antenna 990 to be used for transmitting and receiving signals processed using technologies such as Wi-Fi, WI-MAX, UMG, UWB, television signals, and such other similar signals. In one embodiment, while receiving signals, the antenna 990 may be provided the signals to the T/R switch 980. In one embodiment, while transmitting signals, the antenna 990 may transmit the signals received from the signal transmitter 920. In one embodiment, the T/R switch 980 may comprise intelligence to switch between the signal transmitter 920 and the signal receiver 930.

In one embodiment, the spectrum sensing receiver 970 may detect unutilized portions (holes) of the spectrum and use the holes to meet the demand of the spectrum. In one embodiment, the cognitive radio 950 may receive sensing signals from the spectrum sensing receiver 970 and may generate information on the channels that may be used. In one embodiment, the cognitive radio 950 may provide such information to the channel and power control 940.

In one embodiment, the channel and power control 940 may control the channels and the power consumed by the channels by controlling the signal transmitter 920 and the signal receiver 930. In one embodiment, the power control 940 may support SMST and GMST techniques to provide optimal uplink transmit power to maximize sector throughput and cell-based throughput as described above. In one embodiment, the power control 940 may perform functions as described with reference to the power management block 209 above.

In one embodiment, the signal transmitter 920 may receive signals from the baseband 910 and may modulate the signals using techniques such as phase, amplitude, frequency, and orthogonal frequency division (OFDM) modulation techniques. In one embodiment, the signal receiver 930 may receive signals from the antenna 990 and may demodulate the signals before providing the demodulated signals to the baseband 910. In one embodiment, the baseband 910 may receive signals from the processing blocks of the system and may perform baseband processing before sending the signals to the signal transmitter 920. In one embodiment, the baseband 910 may receive demodulated signals from the signal receiver 930 and may perform baseband processing before providing the signals to the processing blocks of the system 900.

Certain features of the invention have been described with reference to example embodiments. However, the description is not intended to be construed in a limiting sense. Various modifications of the example embodiments, as well as other embodiments of the invention, which are apparent to persons skilled in the art to which the invention pertains are deemed to lie within the spirit and scope of the invention. 

What is claimed is:
 1. An apparatus, comprising: a transmitter coupled to a channel by an uplink, and a power management block coupled to the transmitter to determine an optimal uplink power value using a generalized maximum sector throughput (GMST) technique based on a signal to interference plus noise ratio target (SINR_(Target)), the optimal uplink power value to cause an optimal sector throughput and cell-edge throughput.
 2. The apparatus of claim 1, the SINR_(Target) having a linear relationship with a carrier to interference plus noise ratio (CINR_(Preamble)) of a downlink preamble.
 3. The apparatus of claim 1, the GMST technique comprising tunable parameter coefficients to enhance the sector throughput and cell-edge throughput.
 4. The apparatus of claim 3, the tunable parameter coefficients comprising a parameter to compensate for fractional channel loss.
 5. The apparatus of claim 3, the power management block to determine the SINR_(Target) according to the equation: SINR_(Target)=β×(CINR_(Preamble))^(γ)+α; where α, β, and γ comprise tunable parameter coefficients, γ comprising a parameter to compensate for fractional channel loss.
 6. The apparatus of claim 5, α comprising a value of −1, γ comprising a value of 1, and β comprising a value determined according to the equation: β=1+(1/SINR_(Avg,home)); where SINR_(Avg,home) comprises an average signal to interference plus noise ratio for a home sector.
 7. The apparatus of claim 1, the power management block to limit the SINR_(Target) to be greater than or equal to a minimum value SINR_(Min) and to be less than or equal to a maximum value SINR_(Max), where SINR_(Min) and SINR_(Max) comprise design parameters used to adjust a tradeoff between sector throughput and cell-edge throughput.
 8. The apparatus of claim 1, the power management block to limit an interference over thermal (IoT) noise for a virtual sector to within a specific range.
 9. The apparatus of claim 8, the power management block to limit the IoT noise according to the equation: (P _(New)/CL_(i) ×P _(Noise))≦IoT_(Limit) where IoT_(Limit) comprises a tunable parameter representing a maximum IoT noise for the virtual sector, P_(New) represent a new transmit power, CL_(i) represents a channel loss, and P_(Noise) represents a noise power.
 10. The apparatus of claim 1, the power management block to determine the optimal uplink power value without collecting interference over thermal (IoT) noise from a plurality of neighboring sectors.
 11. A method, comprising: determining a signal to interference plus noise ratio target (SINR_(Target)) according to a generalized maximum sector throughput (GMST) technique, the SINR_(Target) having a linear relationship with a carrier to interference plus noise ratio (CINR_(Preamble)) of a downlink preamble; and determining an uplink power for a mobile node based on the SINR_(Target), the uplink power to optimize sector throughput and cell-edge throughput for a home sector for the mobile node.
 12. The method of claim 11, the GMST technique comprising limiting the SINR_(Target) to be greater than or equal to a minimum value SINR_(Min) and to be less than or equal to a maximum value SINR_(Max), where SINR_(Min) and SINR_(Max) comprise design parameters used to adjust a tradeoff between sector throughput and cell-edge throughput.
 13. The method of claim 11, the GMST technique comprising limiting an interference over thermal (IoT) noise for a virtual sector to within a specific range.
 14. The method of claim 13, the GMST technique comprising limiting the IoT noise according to the equation: (P _(New)/CL_(i) ×P _(Noise))≦IoT_(Limit) where IoT_(Limit) comprises a tunable parameter representing a maximum IoT noise for the virtual sector, P_(New) represent a new transmit power, CL_(i) represents a channel loss, and P_(Noise) represents a noise power.
 15. The method of claim 11, the comprising determining the optimal uplink power value without collecting interference over thermal (IoT) noise from a plurality of neighboring sectors.
 16. The method of claim 11, the GMST technique comprising tunable parameter coefficients to enhance the sector throughput and cell-edge throughput.
 17. The method of claim 16, the tunable parameter coefficients comprising a parameter to compensate for fractional channel loss.
 18. The method of claim 16, the GMST technique comprising determining the SINR_(Target) according to the equation: SINR_(Target)=β×(CINR_(Preamble))^(γ)+α; where α, β, and γ comprise tunable parameter coefficients, γ comprising a parameter to compensate for fractional channel loss.
 19. The method of claim 18, α comprising a value of −1, γ comprising a value of 1, and β comprising a value determined according to the equation: β=1+(1/SINR_(Avg,home)); where SINR_(Avg,home) comprises an average signal to interference plus noise ratio for a home sector.
 20. The method of claim 11, comprising determining the SINR_(Target) without estimating individual channel losses for neighboring sectors. 